Method and system for detecting non-powered video playback devices

ABSTRACT

A method and system for identifying tune data from set top boxes associated with televisions, video monitors, or other video playback devices that are likely powered off. In some embodiments, survival curves are constructed that predict a length of time before a video playback device is powered off after a tuning event. The survival curves are used to predict the likelihood that a video playback device is powered off. Viewership estimates made from tune data reported from set top boxes can be adjusted to take account of the video playback devices that are predicted to be powered off.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of, and claims the benefit of, U.S.patent application Ser. No. 13/081,437, entitled “METHOD AND SYSTEM FORDETECTING NON-POWERED VIDEO PLAYBACK DEVICES,” filed Apr. 6, 2011, whichis incorporated herein by reference in its entirety.

BACKGROUND

In video media distribution systems, estimates are often made of howmany viewers have seen a particular program or were watching aparticular channel. The viewership information can be used for a varietyof purposes, but is often used by networks and other content providersto set rates for show advertisers. Although viewership estimates areaccepted by the industry, advertisers have always sought improvedviewership information to facilitate the selection of programs on whichto advertise. Improved information allows advertisers to ensure thatthey are paying an accurate amount for the audience that they arereaching. Improved information also allows advertisers to better targetdesired audiences that they are trying to reach.

Conventional methods for estimating viewership information include usingspecial receivers that record what programs and channels a user has seenor by asking a selected set of viewers in representative markets torecord their viewing information using paper or electronic logs. Bothmethods can be inaccurate if, for example, the number of viewers thatare sampled is too small or if the sample set does not accuratelyreflect the overall viewership for a wider broadcast region. Moreover,errors can also creep into the records maintained by viewers, therebyproviding erroneous estimates.

An alternative method to estimate viewership is to use the return-pathcapability of video-content hardware platforms already existing in manyTV households. The return-path is used to measure—passively andinvisibly—the viewing choices and behavior of a large subset of theviewers in a given region. There are, however, many challenges inconverting this raw data into useful audience viewership measurements.One of those challenges is to estimate when the return-path device isleft on when the TV or other video monitor is turned off.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system for estimating viewership information.

FIG. 2A illustrates a representative survival curve that can be used topredict if a television is powered on or off.

FIG. 2B illustrates a number of survival curves constructed fordifferent days of the week and time periods in each day.

FIG. 3 is a flowchart of steps performed by a computing system toidentify reliable set top boxes and to construct one or more survivalcurves.

FIG. 4 is a flowchart of steps performed by a computing system toconstruct a number of survival curves.

FIG. 5 illustrates a plot that can be used by a computing system toconstruct a survival curve.

FIG. 6 illustrates how a survival curve can be used to predict if atelevision is powered off from tuning events in a tune data file.

FIG. 7 is a flowchart of steps performed by a computing system toestimate viewership information for a program from tune data associatedwith a number of set top boxes.

DETAILED DESCRIPTION

A system and method to predict when televisions, video monitors, orother video playback devices (each of which is referred to herein as a“video playback device”) have been powered off in order to improve theestimation of viewership of presented content is disclosed herein. Acontent presenter provides tune data available that indicates each timea user interacts with the video device (for example, changes a channel,calls up an interactive program guide etc.) on a video playback device.Such tune data is typically provided by an internal tuner or an externalset top box that is associated with, or incorporated in, the videoplayback device. The tune data is sent back to a central processing andstorage location where a computing system analyzes the tune data toidentify video playback devices associated with set top boxes that arelikely powered off, even though it appears from the tune data that thevideo playback devices are tuned to a particular channel. The tune datafrom set top boxes associated with video playback devices that areidentified as likely being powered off can be factored out of theviewership analysis. For example, the tune data from set top boxesassociated with video playback devices that are likely powered off canbe ignored in calculations of audience viewership.

In some embodiments, the computing system generates “survival curves”that are utilized to estimate when video playback devices are likelypowered off. To generate survival curves, the computing systemidentifies a number of reliable set top boxes from the tune data. Fromthe tune data associated with the identified reliable set top boxes,survival curves are computed that indicate a probability versus timethat a video playback device is powered off after a tuning event. Thesurvival curves are used to estimate subsets of tune data from set topboxes that are associated with video playback devices that are likelypowered off.

Various embodiments of the invention will now be described. Thefollowing description provides specific details for a thoroughunderstanding and an enabling description of these embodiments. Oneskilled in the art will understand, however, that the invention may bepracticed without many of these details or with variations which are notspecified here but which follow from the description in a way that willbe clear to one skilled in the art. Additionally, some well-knownstructures or functions may not be shown or described in detail, so asto avoid unnecessarily obscuring the relevant description of the variousembodiments. The terminology used in the description presented below isintended to be interpreted in its broadest reasonable manner, eventhough it is being used in conjunction with a detailed description ofcertain specific embodiments of the invention.

As shown in FIG. 1, a viewing estimation system 10 includes a computingsystem 50 that is configured to receive tune data from one or morecontent presenters 60. In the embodiment shown, the content presenter 60is a cable television operator that transmits program signals on a cable62. Content presenters include, but are not limited to, satellitetelevision (“digital broadcast satellite”) operators, local or regionalbroadcasters, and distributors of content over other transmission media.A number of subscribers view the program signals on televisions, videomonitors, or other audio/video playback devices 64, 70, 74, 78, 82, 86,(each of which is simply referred to herein as a “video playbackdevice”). Each of the video playback devices is associated with acorresponding internal tuner or external set top box (STB) 68, 72, 76,80, 84, 88 etc. that serves as an interface between the subscriber'svideo playback device and the cable 62 or other transmission means onwhich the television program or other audio-video content istransmitted.

In some embodiments, the set top boxes 68, 72, 76, 80, 84, 88 comprisecable television converters or satellite dish receivers. However, theset top boxes could also be digital video recorders (DVR), gamingconsoles, or other electronic components which allow a user to tune to adesired audio/video stream. Broadly stated, the phrase “set top box” isused herein to refer to any device, component, module, or routine thatenables tune data to be collected from an associated video playbackdevice. Set top boxes may be stand-alone devices or set top boxfunctionality may be incorporated into the video playback devices.

The content presenter 60 has the ability to receive signals indicativeof tuning and other events from each of the set top boxes. The tuningevents can represent such things as channel changes, recording orplaying back programs that are transmitted to a set top box, and changesin play back, such as when a subscriber pauses, fast forwards or rewindsa program or otherwise varies its normal playback. In addition, thetuning events may indicate when a subscriber requests information froman interactive television subscription service. The tuning event data iscollected by the content presenter 60 from each of the set top boxes andis provided to the computing system 50 as tune data. Tune data isassociated with a particular set top box based on, for example, anidentifier in the tune data that identifies the set top box. The tunedata can be transmitted over a computer communication link 30 such as awired or wireless communication link, local area network, wide areanetwork, the Internet, or a telephone link. Alternatively, on a periodicbasis, the tune data could be provided to the computing system 50 on acomputer readable media such as tape drive, DVD, CD-ROM, flash drive,mechanical or solid state hard drive, etc. While the tune data isdepicted as being provided by the content presenter, in some embodimentsthe computing system 50 may receive the tune data from a data aggregatorthat interfaces with a number of content presenters. Moreover, incertain circumstances the computing system may receive the tune datadirectly from the set top boxes.

The computing system 50 analyzes the tune data to estimate viewershipinformation. Authorized users 20, such as content producers,distributors, or advertisers, can access the computing system 50 via thecomputer communication link 30 or by other means to request reportsabout the viewership for a particular channel, program, or timeframe.The computing system 50 calculates the viewership information and canstore the information in a data storage area 52, such as a database, touse when producing one or more reports that can be provided to theauthorized users 20.

In many instances, a subscriber will leave their set top box continuallypowered on but will power off their video playback device when not inuse. For example, a subscriber may leave their cable box powered on as amatter of habit even if they turn off their television. As anotherexample, a subscriber may leave their set top box powered on to record aprogram when they are not home or are unable to watch the program inreal time.

A large number of video playback devices do not provide a signal to theset top box that indicates when the video playback device is poweredoff. Therefore, for these video playback devices, it can appear in thetune data as if a subscriber is actually watching a program or channelbut in fact the video playback device associated with a set top box ispowered off. If the tune data associated with such set top boxes isincluded in the data analyzed to determine viewership information, theresult would overstate the number of viewers that are estimated to bewatching particular programs or channels.

As will be explained in further detail herein, the computing system 50operates to identify one or more video playback devices that are likelyto be powered off at any particular time such that the tune data fromthe set top boxes associated with the identified video playback devicescan be omitted when estimating the viewership information. In someembodiments, the computing system 50 operates to identify one or morereliable set top boxes in the tune data provided from each contentpresenter. In some embodiments, each reliable set top box provides asignal to the content presenter that indicates when a video playbackdevice associated with the set top box is powered off. Such informationmay be provided via a High Definition Multi-Media Interface (HDMI)connection between the set top box and the video playback device or bydetection of another signal provided by the video playback device. Fromthe reliable set top boxes identified, a set of survival curves isconstructed and stored in a memory 54 of the computing system 50.

As will be explained in further detail herein, the survival curvesestimate the likelihood that a video playback device remains powered onat any time between two consecutive tuning events or conversely ispowered off at any time between two consecutive tuning events. In someembodiments, different sets of survival curves are constructed for eachday of the week because the viewership patterns tend to change dependingupon the day of the week and on weekends. Therefore, different survivalcurves can be constructed for different times of the day, as well as fordifferent days of the week and if desired, for different seasons or thelike. Moreover, different survival curves can be constructed fordifferent channels (e.g., television network, cable network etc.) ortypes of programs (e.g., for sit-coms, news shows, movies, sportingevents etc.). In accordance with one embodiment of the disclosedtechnology, the survival curves are used by the computing system 50 toidentify tune data from set top boxes associated with video playbackdevices that are likely powered off.

FIG. 2A illustrates a representative survival curve 100 generated for aparticular time period such as a four hour and 50 minute time intervalbetween consecutive tunes for that particular set top box. The survivalcurve 100 plots the probability versus time that a video playback deviceis powered off at any particular time following the first of twoconsecutive detected tuning events. In the example shown, the survivalcurve 100 is determined for a time period starting at 11:00 p.m. onSunday evenings. In the example survival curve shown, the survival curvepredicts 100 that there is an 84% likelihood that a video playbackdevice associated with a set top box that reports a last tuning event at11:00 p.m. is powered off within 120 minutes after the tuning event.

As shown in FIG. 2B, survival curves 120 can be constructed for each dayof the week starting at each hour of the day. The result is 168 (7×24)sets of survival curves 120 constructed for each hour of the day and foreach day of the week. In addition, each set of survival curves includesa number of individual survival curves constructed for different orvarying periods of time (each period of time associated withcorresponding tune-to-tune intervals). In some embodiments, survivalcurves for time periods of less than 60 minutes are not constructedbecause it has been statistically determined that the difference betweenthe number of video playback devices that are powered on for a full hourand those that are powered off before the end of the hour is minimal. Insome embodiments, separate survival curves are constructed for timeintervals of five minute increases up to a maximum amount of time. Forexample, a survival curve 130 is constructed for a time interval of 60minutes starting at 12 a.m. A survival curve 132 is constructed for atime interval of 65 minutes starting at 12 a.m. A survival curve 134 isconstructed for a time interval of 70 minutes starting at 12 a.m., and asurvival curve 140 is constructed for the maximum time interval startingat 12 a.m. The maximum time interval may be less than 24 hours such as 8hours. Another set of individual survival curves can be constructed forvarious time intervals beginning at 1:00 a.m. and another set isconstructed for various time intervals beginning at 2:00 a.m. etc. foreach hour of the day. Although survival curves are graphically depictedin FIG. 2B, it will be appreciated that a survival curve may berepresented or approximated by, for example, an equation or othermathematical model of the curve or a close fitting to the curve.

FIG. 3 illustrates a process that is performed by the computing system50 to generate the survival curves. Beginning at block 150, thecomputing system receives tune data from one or more content presentersor other sources. In some embodiments, tune data may be received for arelatively long period (e.g., three months) and include tuning eventsfrom millions of set top boxes. At block 152, the computing system 50parses the tune data to identify reliable set top boxes from the tunedata. In some embodiments, the reliable set top boxes are identified bythose set top boxes that report at least one power off event per day andfor which less than 1% of the tune-to-tune event times are 6 hours orlonger. However, it will be appreciated that other criteria could beused to identify reliable set top boxes. At block 154, the computingsystem constructs the survival curves from the tuning events in the tunedata that are associated with the identified reliable set top boxes.

FIG. 4 illustrates a process that is performed by the computing system50 to construct a survival curve in accordance with an embodiment of thedisclosed technology. Although the steps are disclosed in a particularorder for ease of explanation, it will be appreciated that the stepscould be performed in a different order or different steps performed inorder to achieve the functionality described. As will be appreciated bythose skilled in the art, the computing system 50 is configured toexecute a sequence of program steps that are stored on a non-transitory,computer readable media for execution by one or more processors withinthe computing system.

As previously shown in FIG. 2B, sets of survival curves for varyingsurvival time intervals are constructed starting for example, withineach hour and for each day of the week. Returning to FIG. 4, at block170 the computing system 50 analyzes the set top box tune data todetermine reliable set top boxes that are associated with a first tuningevent occurring near the beginning of a survival time interval and asecond tuning event occurring near the end of the survival timeinterval. For example, if a 120 minute survival curve is to be computedfor Tuesdays starting at 8:00 p.m., the computing system identifiesreliable set top boxes reporting a first tuning event within the hourfrom 8:00 p.m. to 8:59:59 p.m. (the start of the survival time) and asecond tuning event from the same set top box that occurs, for example,between 120 and 125 minutes later (the end of the survival time). Atblock 172, the computing system analyzes the times at which the videoplayback devices associated with the identified reliable set top boxesare powered off. In some embodiments, the power off information isincluded in the tuning event reported from the set top boxes. Such datacan be based on HDMI signals received from the video playback device orother signals that indicate if the video playback device has beenpowered off. Which video playback devices are powered off can becontinuously recorded or can be grouped within small time intervals,such as every five minutes. For example, FIG. 5 shows a graph 190 thatplots the number of set top boxes that are determined to be powered offduring each of a number of five minute intervals beginning at the starttime of the survival time period up to the end time of the survival timeperiod (75 minutes for the example shown). In the example shown, 200video playback devices are determined to have been powered off in thefirst five minutes, 225 video playback devices are determined to havebeen powered off in the next five minutes, etc.

At block 174, the computing system 50 determines the percentage of videoplayback devices associated with the identified reliable set top boxesthat are powered off in each time interval. The results are stored in amemory or on a computer readable media as the survival curve for thesurvival time period in question at block 176.

At block 180, the computing system 50 determines if all the survivaltime periods have been analyzed. If so, processing is complete. If not,the start and end times for the survival time period are adjusted atblock 182 and processing returns to block 170 to compute anothersurvival curve. The computing system 50 repeats blocks 170-176 togenerate the desired sets of survival curves. For example, the computingsystem may construct survival curves starting at the beginning of eachhour, for each day of the week, for different network and program types,and for survival intervals that range between 1 and 6 hours inincrements of 5 minutes.

Once the set of survival curves are constructed from the tune dataassociated with the reliable set top boxes, the survival curves can beused to identify those video playback devices that do not report a poweroff event but are statistically likely to be powered off.

FIG. 6 illustrates an example where tune data associated with set topbox number 1016278 has tuning events that occur 134 minutes apart. Topredict whether a video playback device associated with the set top boxnumber 1016278 is powered on or is powered off, the computing system 50identifies a previously-generated survival curve having a beginning timeclosest to the first tuning event for the set top box in question and anend time which is closest to the second tuning event. In the exampleshown, a survival curve 210 having a 135 minute time interval isselected. Once the appropriate survival curve has been selected, thecomputing system implements a statistical technique to determine whereon the survival curve the video playback device associated with the settop box number 1016278 is likely to fall.

In some embodiments of the disclosed technology, the computing system 50uses a Monte Carlo technique to guarantee that the probabilitydistribution function of adjusted tune lengths matches the empiricaldistribution determined from the reliable set top boxes. The Monte Carlotechnique is implemented by selecting a uniformly-distributed randomnumber between zero and one that represents the probability that thecorresponding video playback device is powered off. In the exampleshown, the random number generated is 0.72 (e.g., a 72% likelihood thatthe video playback device is powered off). Next, the survival curve 210is analyzed to determine what time corresponds to the randomly selectedprobability that the video playback device is powered off. In theexample shown in FIG. 6, the 72% likelihood that a video playback deviceis powered off corresponds to a time period of 83 minutes after thefirst tuning event. Therefore, the tune data for the video playbackdevice associated with set top box 1016278 can be assumed to be validfor the first 83 minutes and invalid for minutes 83-134. When applied todata representing a large number of set top boxes, the disclosedstatistical technique closely approximates actual tune information.Although the disclosed embodiment uses a Monte Carlo technique topredict whether a video playback device is powered on or is powered off,it will be appreciated that other statistical techniques could also beused.

FIG. 7 illustrates a process that can be performed by the computingsystem 50 in order to analyze received tune data in order to estimateviewership information. For example, an authorized user of the computingsystem 50 may be interested in estimating the number of viewers who sawan episode of the show “Modern Family,” which airs on ABC on Wednesdaynights at 8:00 p.m. Pacific time. To estimate the number of likelyviewers, at a block 250 the computing system 50 receives tune datacovering the period of interest from one or more content presenters (orrecalls the tune data from a computer readable media). At a block 252,the computing system 50 searches the tune data to identify those set topboxes that appear to have been tuned to the channel on which the programin question was presented. By doing so, the computing system determinesa maximum number of video playback devices that are potentially tuned tothe program of interest. The maximum number then needs to be reduced bythe number of video playback devices that are predicted to be poweredoff during any portion of the relevant period.

At a block 254, the computing system predicts whether each of theidentified set top boxes associated with a video playback device waslikely powered on or was likely powered off during the relevant period.In some embodiments, the computing system estimates if the videoplayback devices represented in the tune data were powered on or werepowered off by identifying tuning events reported by the associated settop box that include the time during which the show was broadcast. Forexample, if the show Modern Family is presented on cable channel 40 at 8p.m. and is one hour long, then the computing system 50 can search thetune data for set top boxes tuned to channel 40 at some time between 8and 9 p.m. For each identified set top box, the closest tuning eventsare identified that fall before, during, or after the period duringwhich the program was presented. In particular, the computing system 50may search for first tuning events that start before the end of theprogram and second tuning events that start after the start of theprogram. For example, a first tuning event for a set top box may be totune to channel 40 at 7:50 p.m. and a second tuning event may occur at9:05. The time between the tuning events is then determined (e.g., 75minutes) and the survival curve that begins nearest the first tuningevent is selected having a survival time length that includes the secondtuning event. In this example, a survival curve starting at 8 p.m. isselected having a length of 75 minutes. Once the computing system 50 hasselected a survival curve, the computing system uses the selected curveto predict the time at which the video playback device associated withthe identified set top box is likely powered off. Any viewershipdeterminations made by the computing system 50 can then be adjusted forthe times during which the identified video playback devices arepredicted to be powered off. At a block 256, other adjustments may bemade to the viewership data before it is presented to an authorizeduser. For example, the selected set of data may represent only certainmarkets or only portions of the markets. In order to present completeviewership data, the computing system 50 would therefore need toextrapolate the results for those markets or portions of markets forwhich no viewership data is available. At a block 258 the computingsystem presents the resulting viewership information to authorizedusers. The information may be presented, for example, via an onlineportal or other user interface, transferred via email or otherelectronic delivery system or printed in hard copy.

In some embodiments, tuning events caused by the automatic recording ofprograms (e.g., programs that are recorded by virtue of a subscriber'sprior record settings of a DVR) can be distinguished from tuning eventsassociated with instructions received from a subscriber. Incircumstances in which a program was recorded automatically, the tunedata that is received by the computing device may include an indicationthat a show was automatically recorded. The tuning events associatedwith these automatic channel changes can therefore be factored in whenestimating the number of viewers who watched a show as it was aired. Insome cases, it may be necessary to revise the viewership numbersdownward since not every person that records a show will ultimatelywatch the recording.

Embodiments of the subject matter described in this specification can beimplemented as one or more computer programs, i.e., one or more modulesof computer program instructions, encoded on computer storage medium forexecution by, or to control the operation of, data processing apparatus.A computer storage medium can be, or can be included in, anon-transitory computer-readable storage device, a computer-readablestorage substrate, a random or serial access memory array or device, ora combination of one or more of them. Moreover, while a computer storagemedium is not a propagated signal, a computer storage medium can be asource or destination of computer program instructions encoded in anartificially generated propagated signal. The computer storage mediumalso can be, or can be included in, one or more separate physicalcomponents or media (e.g., multiple CDs, disks, or other storagedevices). The operations described in this specification can beimplemented as operations performed by a processor on data stored on oneor more computer-readable storage devices or received from othersources.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, declarative orprocedural languages, and it can be deployed in any form, including as astand alone program or as a module, component, subroutine, object, orother unit suitable for use in a computing environment. A computerprogram may, but need not, correspond to a file in a file system. Aprogram can be stored in a portion of a file that holds other programsor data (e.g., one or more scripts stored in a markup languagedocument), in a single file dedicated to the program in question, or inmultiple coordinated files (e.g., files that store one or more modules,sub programs, or portions of code). A computer program can be deployedto be executed on one computer or on multiple computers that are locatedat one site or distributed across multiple sites and interconnected by acommunication network.

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random access memory or both. The essential elements of a computer area processor for performing actions in accordance with instructions andone or more memory devices for storing instructions and data. Generally,a computer will also include, or be operatively coupled to receive datafrom or transfer data to, or both, one or more mass storage devices forstoring data, e.g., magnetic, magneto optical disks, or optical disks.However, a computer need not have such devices. Moreover, a computer canbe embedded in another device, e.g., a mobile telephone, a personaldigital assistant (PDA), a mobile audio or video player, a game console,a Global Positioning System (GPS) receiver, or a portable storage device(e.g., a universal serial bus (USB) flash drive), to name just a few.Devices suitable for storing computer program instructions and datainclude all forms of non volatile memory, media and memory devices,including by way of example semiconductor memory devices, e.g., EPROM,EEPROM, and flash memory devices; magnetic disks, e.g., internal harddisks or removable disks; magneto optical disks; and CD ROM and DVD-ROMdisks. The processor and the memory can be supplemented by, orincorporated in, special purpose logic circuitry.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a computerhaving a display device, e.g., an LCD (liquid crystal display), LED(light emitting diode), or OLED (organic light emitting diode) monitor,for displaying information to the user and a keyboard and a pointingdevice, e.g., a mouse or a trackball, by which the user can provideinput to the computer. In some implementations, a touch screen can beused to display information and to receive input from a user. Otherkinds of devices can be used to provide for interaction with a user aswell; for example, feedback provided to the user can be any form ofsensory feedback, e.g., visual feedback, auditory feedback, or tactilefeedback; and input from the user can be received in any form, includingacoustic, speech, or tactile input. In addition, a computer can interactwith a user by sending documents to and receiving documents from adevice that is used by the user; for example, by sending web pages to aweb browser on a user's client device in response to requests receivedfrom the web browser.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back end component,e.g., as a data server, or that includes a middleware component, e.g.,an application server, or that includes a front end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back end, middleware, or front end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), an inter-network (e.g., the Internet), andpeer-to-peer networks (e.g., ad hoc peer-to-peer networks).

The computing system can include any number of clients and servers. Aclient and server are generally remote from each other and typicallyinteract through a communication network. The relationship of client andserver arises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. In someembodiments, a server transmits data (e.g., an HTML page) to a clientdevice (e.g., for purposes of displaying data to and receiving userinput from a user interacting with the client device). Data generated atthe client device (e.g., a result of the user interaction) can bereceived from the client device at the server.

From the foregoing, it will be appreciated that specific embodiments ofthe invention have been described herein for purposes of illustration,but that various modifications may be made without deviating from thescope of the invention. Accordingly, the invention is not limited exceptas by the appended claims.

We claim:
 1. A computing system to facilitate video playback deviceviewing data analysis, comprising: at least one processor; a memorycomprising instructions executable by the at least one processor to:receive tune data indicative of content tuned to by a number of videoplayback devices, the tune data associated with each video playbackdevice including an identification associated with the video playbackdevice and a plurality of tuning events, each tuning event including atime of the tuning event and a corresponding content identifier that wastuned at the tuning event; identify a first plurality of video playbackdevices for which power-off event data is available based on the tunedata; analyze the power-off event data to determine one or more times atwhich the first plurality of video playback devices were powered off;determine a percentage of the first plurality of video playback devicesthat were powered off within at least one time interval following atuning event; generate a survival curve based upon the percentage; andassess tune data associated with a particular video playback device by:selecting a random number corresponding to a probability in the survivalcurve; identifying a time from the survival curve corresponding to theprobability; categorizing tune data before the identified time as valid;and categorizing tune data after the identified time as invalid.
 2. Thecomputing system of claim 1, wherein power-off event data is notavailable for the video playback device not included in the firstplurality of video playback devices.
 3. The computing system of claim 2,wherein the survival curve is one of a plurality of survival curvesassociated with different portions of a day.
 4. The computing system ofclaim 1, wherein the survival curve depicts a probability versus time.5. The computing system of claim 1, wherein determining the percentagecomprises recording a probability that a video playback device is turnedoff corresponding to a point in time.
 6. The computing system of claim1, wherein identifying the first plurality of video playback devicescomprises identifying video playback devices associated with reports ofat least one power off event per day and for which less than 1% of thetune-to-tune event times are 6 hours or longer.
 7. The computing systemof claim 1, wherein the instructions are further executable by the atleast one processor to ensure that a probability distribution functionof adjusted tune lengths not associated with the first plurality ofvideo playback devices corresponds to an empirical distributiondetermined from the first plurality of video playback devices.
 8. Anon-transitory, computer readable medium with instructions storedthereon that are executable by at least one processor to: receive tunedata indicative of content tuned to by a number of video playbackdevices, the tune data associated with each video playback deviceincluding an identification associated with the video playback deviceand a plurality of tuning events, each tuning event including a time ofthe tuning event and a corresponding content identifier that was tunedat the tuning event; identify a first plurality of video playbackdevices for which power-off event data is available based on the tunedata; analyze the power-off event data to determine one or more times atwhich the first plurality of video playback devices were powered off;determine a percentage of the first plurality of video playback devicesthat were powered off within at least one time interval following atuning event; generate a survival curve based upon the percentage; andassess tune data associated with a particular video playback device by:selecting a random number corresponding to a probability in the survivalcurve; identifying a time from the survival curve corresponding to theprobability; categorizing tune data before the identified time as valid;and categorizing tune data after the identified time as invalid.
 9. Acomputer-implemented method of analyzing tune data, comprising:receiving, at a computing system, tune data indicative of content tunedto by a number of video playback devices, the tune data associated witheach video playback device including an identification associated withthe video playback device and a plurality of tuning events, each tuningevent including a time of the tuning event and a corresponding contentidentifier that was tuned at the tuning event; identifying a firstplurality of video playback devices for which power-off event data isavailable based on the tune data; analyzing the power-off event data todetermine one or more times at which the first plurality of videoplayback devices were powered off; determining a percentage of the firstplurality of video playback devices that were powered off within atleast one time interval following a tuning event; generate a survivalcurve based upon the percentage; and assess tune data associated with aparticular video playback device by: selecting a random numbercorresponding to a probability in the survival curve; identifying a timefrom the survival curve corresponding to the probability; categorizingtune data before the identified time as valid; and categorizing tunedata after the identified time as invalid.
 10. The non-transitorycomputer readable medium of claim 8, wherein power-off event data is notavailable for the video playback device not included in the firstplurality of video playback devices.
 11. The non-transitory computerreadable medium of claim 8, wherein the survival curve is one of aplurality of survival curves associated with different portions of aday.
 12. The non-transitory computer readable medium of claim 8, whereinthe survival curve depicts a probability versus time.
 13. Thenon-transitory computer readable medium of claim 8, wherein determiningthe percentage comprises recording a probability that a video playbackdevice is turned off corresponding to a point in time.
 14. Thenon-transitory computer readable medium of claim 8, wherein identifyingthe first plurality of video playback devices comprises identifyingvideo playback devices associated with reports of at least one power offevent per day and for which less than 1% of the tune-to-tune event timesare 6 hours or longer.
 15. The non-transitory computer readable mediumof claim 8, wherein the instructions are further executable by the atleast one processor to ensure that a probability distribution functionof adjusted tune lengths not associated with the first plurality ofvideo playback devices corresponds to an empirical distributiondetermined from the first plurality of video playback devices.
 16. Thecomputer-implemented method of claim 9, wherein power-off event data isnot available for the video playback device not included with theidentified first plurality of video playback devices.
 17. Thecomputer-implemented method of claim 9, wherein the survival curve isone of a plurality of survival curves associated with different portionsof a day.
 18. The computer-implemented method of claim 9, wherein thesurvival curve depicts a probability versus time.
 19. Thecomputer-implemented method of claim 9, wherein determining thepercentage comprises recording a probability that a video playbackdevice is turned off corresponding to a point in time.
 20. Thecomputer-implemented method of claim 9, wherein identifying the firstplurality of video playback devices comprises identifying video playbackdevices associated with reports of at least one power off event per dayand for which less than 1% of the tune-to-tune event times are 6 hoursor longer.
 21. The computer-implemented method of claim 9, furthercomprising ensuring that a probability distribution function of adjustedtune lengths not associated with the first plurality of video playbackdevices corresponds to an empirical distribution determined from thefirst plurality of video playback devices.
 22. The computing system ofclaim 7, wherein the survival curve is one of a plurality of survivalcurves associated with different portions of a day and wherein theempirical distribution and the probability distribution function ofadjusted tune lengths comprise tune lengths within the portion of theday associated with the survival curve.
 23. The non-transitory computerreadable medium of claim 15, wherein the survival curve is one of aplurality of survival curves associated with different portions of a dayand wherein the empirical distribution and the probability distributionfunction of adjusted tune lengths comprise tune lengths within theportion of the day associated with the survival curve.
 24. Thecomputer-implemented method of claim 21, wherein the survival curve isone of a plurality of survival curves associated with different portionsof a day and wherein the empirical distribution and the probabilitydistribution function of adjusted tune lengths comprise tune lengthswithin the portion of the day associated with the survival curve.